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Design of character recognition system based on LabVIEW

Published:29 October 2021Publication History
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References

  1. Huang Fenglei, Ruan Weipeng. Design of Digital Identification System Based on NI Vision Assiant Multimeter [J]. Industrial Metrology,2016,26(S2):8-10.Google ScholarGoogle Scholar
  2. Cai Zhaohu, Li Ketian, Liu Ji 'an, Chen Tieqiang, Yin Bo. Chip character recognition system based on LabVIEW and IMAQ [J]. Mechanical and Electrical Engineering Technology,2009,38(04):78-80+109+131.Google ScholarGoogle Scholar
  3. Fan Chunling, Ding Yuhuan, Sui Yelong. Face recognition system in classroom scene based on LabVIEW platform [J]. Journal of Qingdao University of Science and Technology (Natural Science Edition),2012,33(05):535-540.Google ScholarGoogle Scholar
  4. Yang Meicheng. Research on RMB Crown Character Recognition System Based on LabVIEW [J]. Wireless Internet Technology,2017(05):41-43.Google ScholarGoogle Scholar
  5. JI Fujuan, HUANG Chang. Digital recognition of digital tube based on LabVIEW [J]. Information Technology,2012,36(12):114-115+120.Google ScholarGoogle Scholar
  6. Cheng Hao. Research on character image recognition system based on virtual instrument [D]. Agricultural University of Hebei,2006.Google ScholarGoogle Scholar
  7. Li Yan, Mao Hanping, Chen Shuren. Real-time weed identification and location in cotton field based on LabVIEW [J]. Journal of Agricultural Mechanization Research,2011,33(02):134-138.Google ScholarGoogle Scholar
  8. Liu Chunying, Wu Dehua. Research and Application of License Plate Image Recognition Technology Based on LabVIEW [J]. Journal of Langfang Normal University (Natural Science Edition),2010,10(02):45-47.Google ScholarGoogle Scholar
  9. NI Nan. Design of Digital Multi-purpose Meter Dial Character Recognition System [D]. Xidian University,2017.Google ScholarGoogle Scholar
  10. [10] Xiao Jian. OCR character recognition based on learning [J]. Computer era,2018(07):48-51.Google ScholarGoogle Scholar
  11. Lu Changchang, Ning Shaowen, Tang Dechang. Research and application of optical character recognition technology (OCR) [J]. China Strategic Emerging Industries,2018(28):1-3.Google ScholarGoogle Scholar
  12. Wang Wenping. Chip character recognition based on Halcon [D]. Dalian Jiaotong University,2018.Google ScholarGoogle Scholar
  13. Hu Hanjing, Wang Xiaoni. Character Recognition of RBF Neural Network Based on Matlab7.0 [J]. Shanxi Youth,2018(20):211.Google ScholarGoogle Scholar
  14. Hao Hui, Halimulati Maimaiti, Qiao Sachula, Su Peipei. Quantitative analysis of character recognition research status and development trend [J]. Modern Electronic Technology,2018,41(22):154-158.Google ScholarGoogle Scholar
  15. Wu Weiwei, Wang Xiaohong, Zhou Yanan. Two Improved Template Matching Algorithms in Character Recognition [J]. Sensor World,2008(06):35-37.Google ScholarGoogle Scholar

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  • Published in

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    ICIIP '21: Proceedings of the 6th International Conference on Intelligent Information Processing
    July 2021
    347 pages
    ISBN:9781450390637
    DOI:10.1145/3480571

    Copyright © 2021 ACM

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    Publication History

    • Published: 29 October 2021

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